Reluctant migrants: socialization patterns among Salvadorian children
Bibliographic record
Abstract
Seven major Hispanic communities have contributed to the multicultural shape of Australia, Salvadorians being one of the prominent groups. As in the United States and Canada, immigration to Australia from El Salvador peaked in the mid 1980s during its civil war. +is chapter describes the schooling experiences in Australia of 19 newly arrived Salvadorian children to Australia. It explores their initial schooling experiences, language use, and socialization patterns. +is group represents an unusual subset of the total immigrant population insofar as these were the children obliged to accompany their migrant parents, who themselves were reluctant migrants, driven to immigrate by war and its consequences. +is study is based on the analysis and interpretation of adult retrospective accounts of students who migrated to Australia between 1985 and 2002 as 8 to 17-year-olds. It discusses the factors that impacted on the socialization process of these young migrants in Australian schools. Overall, it was found that English language competence played an important role in the socialization process of these young Spanish-speaking migrants. Many of the participants experienced great di*culty during their initial school integration in Australia due to their lack of English competence. Bilingual (Spanish-English) teachers and peer students played a major role in easing the transition of these young Spanish speaking migrants into English-speaking schools in Australia. +e strategies proposed by the participants to support Spanish-speaking migrants in their integration into Australian society are reported.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".